DBMS > Interbase vs. Microsoft SQL Server vs. RRDtool vs. Splice Machine vs. Splunk

System Properties Comparison Interbase vs. Microsoft SQL Server vs. RRDtool vs. Splice Machine vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Light-weight proven RDBMS

originally from Borland

Microsofts flagship relational DBMS

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Analytics Platform for Big Data

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

www.embarcadero.com/products/interbase

www.microsoft.com/en-us/sql-server

oss.oetiker.ch/rrdtool

splicemachine.com

www.splunk.com

Technical documentation

docs.embarcadero.com/products/interbase

learn.microsoft.com/en-US/sql/sql-server

oss.oetiker.ch/rrdtool/doc

splicemachine.com/how-it-works

docs.splunk.com/Documentation/Splunk

Developer

Embarcadero

Microsoft

Tobias Oetiker

Splice Machine

Splunk Inc.

Initial release

1984

1989

1999

2014

2003

Current release

InterBase 2020, December 2019

SQL Server 2022, November 2022

1.8.0, 2022

3.1, March 2021

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL V2 and FLOSS

Open Source

AGPL 3.0, commercial license available

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Implementations in Java (e.g. RRD4J) and C# available

Java

Server operating systems

Android
iOS
Linux
OS X
Windows

Linux
Windows

HP-UX
Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

export as XML data possible

yes

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

in-process shared library
Pipes

JDBC
Native Spark Datasource
ODBC

HTTP REST

Supported programming languages

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

yes, but depending on the SQL-Server Edition

none

Multi-source replication
Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

by using the rrdcached daemon

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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